Image processor, image formation device, image processing method, and computer-readable medium

ABSTRACT

An image processor includes: a gradation value acquisition unit that acquires a gradation value of a pixel of interest which is a pixel sequentially selected as a target of a binarization process from input image data represented by pixels of M gradations, wherein M≧3; and a pattern determination unit that determines a filling pattern of a group of pixels of output image data corresponding to the pixel of interest according to a corrected gradation value acquired by adding, to the gradation value of the pixel of interest, an error value diffused from a pixel at a periphery of the pixel of interest, wherein the filling pattern includes at least a first pattern in which a predetermined plurality of pixels are filled and which forms a core of a dot and a third pattern in which substantially no pixel is filled and the pattern determination unit determines the filling pattern to be one of the first pattern and the third pattern according to a size relationship between the corrected gradation value and a predetermined threshold value which spatially varies in a periodic manner.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on and claims priority under 35 USC 119 fromJapanese Patent Application No. 2007-224729 filed on Aug. 30, 2007.

BACKGROUND

1. Technical Field

The present invention relates to an image processor, an image formationdevice, an image processing method, and a computer-readable medium.

2. Related Art

According to a known technique, input image data represented by pixelswith M (M≧3) gradations are converted to output image data representedwith pixels with 2 gradations, through an error diffusion process.

SUMMARY

According to an aspect of the present invention, there is provided animage processor including: a gradation value acquisition unit thatacquires a gradation value of a pixel of interest which is a pixelsequentially selected as a target of a binarization process from inputimage data represented by pixels of M gradations, wherein M≧3; and apattern determination unit that determines a filling pattern of a groupof pixels of output image data corresponding to the pixel of interestaccording to a corrected gradation value acquired by adding, to thegradation value of the pixel of interest, an error value diffused from apixel at a periphery of the pixel of interest, wherein the fillingpattern includes at least a first pattern in which a predeterminedplurality of pixels are filled and which forms a core of a dot and athird pattern in which substantially no pixel is filled and the patterndetermination unit determines the filling pattern to be one of the firstpattern and the third pattern according to a size relationship betweenthe corrected gradation value and a predetermined threshold value whichspatially varies in a periodic manner.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments of the present invention will be described indetail by reference to the following figures, wherein:

FIG. 1 is a block diagram showing a structure of an image processoraccording to an exemplary embodiment of the present invention;

FIG. 2 is a block diagram showing an example of a specific structure ofan image processor according to an exemplary embodiment of the presentinvention;

FIG. 3 is a flowchart showing an example of a conversion process in anexemplary embodiment of the present invention;

FIG. 4 is a diagram showing an example of an error value of a peripheralpixel;

FIG. 5 is a diagram showing an example of a diffusion error coefficientcorresponding to a peripheral pixel;

FIG. 6 is a diagram showing an example of a black core pattern;

FIG. 7 is a diagram showing an example of a white core pattern;

FIG. 8 is a diagram showing a first determination map;

FIG. 9 is a diagram showing a second determination map;

FIG. 10 is a flowchart showing an example of a process for determining afilling pattern;

FIG. 11 is a diagram showing an example in which a pixel of interest isconverted to a black growth pattern when a group of pixels correspondingto a reference pixel above and to the left of the pixel of interest is agroup of pixels of a black core pattern;

FIG. 12 is a diagram showing an example list when no group of pixels ofa black core pattern is present among the groups of pixels correspondingto three reference pixels adjacent to the pixel of interest;

FIG. 13 is a diagram showing an example of a threshold value matrix;

FIG. 14 is a diagram showing an example of a correspondence relationshipbetween a pixel of input image data and a threshold value;

FIG. 15 is a diagram showing an example in which a pixel of interest isconverted to a white growth pattern when a group of pixels correspondingto the reference pixel above and to the left of the pixel of interest isa group of pixels of a white core pattern;

FIG. 16 is a diagram showing an example when no group of pixels of awhite core pattern is present among the groups of pixels correspondingto three reference pixels adjacent to the pixel of interest;

FIG. 17 is a diagram showing an example setting of a correspondencerelationship between a density value of the pixel of interest and anumber of black pixels in a black core pattern or a number of whitepixels in a white core pattern;

FIG. 18 is a diagram showing an example of a result of the binarizationprocess in a third exemplary embodiment;

FIG. 19 is a diagram showing an example of a result of the binarizationprocess in a comparative example; and

FIG. 20 is a schematic structural diagram showing a structure of animage formation device including an image processor according to anexemplary embodiment of the present invention.

DETAILED DESCRIPTION

Exemplary embodiments of the present invention will now be describedwith reference to the drawings.

First Exemplary Embodiment

FIG. 1 is a block diagram showing a structure of an image processor 10according to a first exemplary embodiment of the present invention. Theimage processor 10 converts input image data represented by pixels withM gradations (M≧3) into output image data represented by pixels with twogradations.

In one configuration, the image processor 10 is realized by cooperationof a hardware resource and software. For example, as shown in FIG. 2,the image processor 10 includes a CPU (Central Processing Unit) 1, arecording medium 2 such as a ROM (Read Only Memory), and a main memory3. The functions of the image processor 10 are realized by an imageprocessing program recorded on the recording medium 2 being read intothe main memory 3 and executed by the CPU 1. The image processingprogram may be provided in a recorded form on a recording medium such asa CD-ROM or may alternatively be provided through communication as adata signal. In another configuration, the image processor 10 isrealized with only hardware.

In FIG. 1, the image processor 10 has a reception unit 11, a conversionunit 12, and an output unit 13.

The reception unit 11 receives input of input image data represented bypixels of M gradations (M≧3). More specifically, the input image dataincludes multiple pixels each having a gradation value of M values. Theinput image data are also called image data represented with multiplevalues. The reception unit 11 receives input image data using, forexample, a RAM (Random Access Memory).

The conversion unit 12 applies a predetermined conversion process to theinput image data received by the reception unit 11 and converts theinput image data into output image data represented by pixels of twogradations.

The output unit 13 outputs the output image data acquired by theconversion unit 12 to the outside (for example, to another device andanother software module). For example, the output unit 13 outputs theoutput image data to a RAM.

The predetermined conversion process of the conversion unit 12 will nowbe described.

The conversion unit 12 includes a gradation value acquisition unit 12 aand a pattern determination unit 12 b.

The gradation value acquiring unit 12 a acquires a gradation value of apixel sequentially selected from the input image data as a target ofbinarization process (hereinafter referred to as a “pixel of interest”).

The “pixel of interest” is, for example, selected from the input imagedata in which pixels are arranged in a matrix form along a main scandirection and a sub-scan direction, in a predetermined order along themain scan direction and the sub-scan direction.

The pattern determination unit 12 b determines a filling pattern of agroup of pixels of the output image data corresponding to the pixel ofinterest according to a corrected gradation value acquired by adding anerror value diffused from peripheral pixels of the pixel of interest tothe gradation value of the pixel of interest acquired by the gradationvalue acquisition unit 12 a.

The “error value diffused from peripheral pixels of the pixel ofinterest” is a diffused error in the error diffusion process, and is, ina more specific configuration, an error value acquired by weighting anerror value of a pixel in the periphery of the pixel of interest(hereinafter referred to as “peripheral pixel”) by a predetermined errordiffusion coefficient. The “error value of the peripheral pixel” is anerror value between the corrected gradation value of the peripheralpixel and the gradation value represented by the filling patterndetermined for the peripheral pixel. For example, the error value of theperipheral pixel is calculated after the determination of the fillingpattern when the peripheral pixel is set as the pixel of interest and isstored in an error value storage 21. The “error diffusion coefficient”is a coefficient which is set by reference to a relative positionbetween the pixel of interest and the peripheral pixel, and is set, inone configuration, so that the weight is increased as the distance tothe pixel of interest is shortened. The error diffusion coefficient maybe, for example, determined in consideration of the gradationreproducibility of the image or the like. For example, the errordiffusion coefficient is stored in an error diffusion coefficientstorage 22 in advance.

The “corrected gradation value” is a value acquired by adding an errorvalue diffused from the peripheral pixel to the gradation value of thepixel of interest, and is calculated, for example, in the followingmanner. When the gradation value of the pixel of interest P is Cin, theerror values of N (N≧1) peripheral pixels Pn (n=1, 2, . . . , N) are En(n=1, 2, . . . , N), and the error diffusion coefficients correspondingto the peripheral pixels Pn are Dn (n=1, 2, . . . , N), the correctedgradation value Ca can be acquired by the following equation (1).

$\begin{matrix}{{Ca} = {{Cin} + {\sum\limits_{n = 1}^{N}\; {{Dn} \cdot {En}}}}} & \left\lbrack {{Equation}\mspace{14mu} 1} \right\rbrack\end{matrix}$

For example, the conversion unit 12 reads the error value En of theperipheral pixel from the error value storage 21, reads the errordiffusion coefficient Dn from the error diffusion coefficient storage22, and calculates the corrected gradation value Ca.

The corrected gradation value may include a correction other than theaddition of the error value as described above. For example, thecorrected gradation value may be a value acquired by adding an errorvalue diffused from the peripheral pixel and a random number to thegradation value of the pixel of interest.

The “group of pixels” is a collection of multiple pixels correspondingto a pixel in the input image data, and is, for example, multiple pixelsarranged in a matrix form.

The “filling pattern of the group of pixels” is a pattern characterizedby whether or not each pixel of the group of pixels is to be filled. Thepixel to be filled is also referred to as a pixel to be colored, an ONpixel, a switched ON pixel, a black pixel, or the like, and is, forexample, a pixel with a gradation value of “1”. Meanwhile, the pixelwhich is not filled is also referred to as a non-colored pixel, an OFFpixel, a switched OFF pixel, a white pixel, or the like, and is, forexample, a pixel with a gradation value of “0”. In the followingdescription, the filled state is referred to as “black” and thenon-filled state is referred to as “white”.

The filling patterns include a first pattern in which predeterminedmultiple pixels are filled and which forms a core of a dot, a secondpattern in which a number of pixels are filled, the number correspondingto the corrected gradation value, and which forms a dot along with thefirst pattern, and a third pattern in which substantially no pixel isfilled.

The first pattern forms a core of a black dot, and, in the followingdescription, is referred to as a “black core pattern”. Morespecifically, the black core pattern is a pattern in which apredetermined number of pixels at predetermined positions are filled andthe other pixels are not filled. The number of filled pixels in theblack core pattern defines the minimum size of the black dot and may beset, for example, in consideration of the gradation reproducibility.

The second pattern is a pattern for growing the black dot, and, in thefollowing description, is referred to as a “black growth pattern”. Morespecifically, the black growth pattern is a pattern in which one or morepixels are filled corresponding to the corrected gradation value and theother pixels are not filled, in order to increase a size of the blackdot.

The third pattern is an overall white pattern and, in the followingdescription, is referred to as an “all-white pattern”. Morespecifically, the all-white pattern is a pattern in which none of thepixels is filled. However, it is sufficient that the all-white patternis a pattern in which substantially none of the pixels is filled, and,thus, the all-white pattern may be a pattern in which a small number ofpixels are filled in to such a degree as to not have an effect on theimage.

From the viewpoint of executing a superior process in a high densityregion, the filling patterns may include a white core pattern whichforms a core of a white dot and a white growth pattern which grows thewhite dot. Here, the white core pattern is a pattern in whichpredetermined multiple pixels are not filled, and, more specifically, isa pattern in which a predetermined number of pixels at predeterminedpositions are not filled and the other pixels are filled. The whitegrowth pattern is a pattern in which a number of pixels are not filled,the number corresponding to the corrected gradation value, and whichforms a white dot along with the white core pattern. More specifically,the white growth pattern is a pattern in which one or more pixels arenot filled corresponding to the corrected gradation value and the otherpixels are filled, in order to increase a size of the white dot.

In addition, from the viewpoint of executing a superior process in thehigh density region, the filling patterns may include an all blackpattern in which substantially all pixels are filled.

The collection of the black pixel of the black core pattern and theblack pixel of the black growth pattern and the collection of the whitepixel of the white core pattern and the white pixel of the white growthpattern form a black dot and a white dot, respectively, and thecollections are also known as “clusters”.

The pattern determination unit 12 b determines the filling pattern inthe following manner.

The pattern determination unit 12 b determines the filling pattern to bethe black growth pattern when a pixel which is determined as the blackcore pattern is present among predetermined pixels adjacent to the pixelof interest. Here, the predetermined pixels adjacent to the pixel ofinterest (hereinafter referred to as “reference pixels”) are one or moreprocessed pixels, and the determination of which adjacent pixel of whichposition of the pixel of interest is to be set as the reference pixelmay be made so that the core of the black dot represented by the blackcore pattern is grown by the black growth pattern.

The pattern determination unit 12 b determines the filling pattern to bethe black core pattern or the all-white pattern according to a sizerelationship between the corrected gradation value and a predeterminedthreshold value when no pixel in the reference pixels is determined asthe black core pattern. More specifically, the pattern determinationunit 12 b determines the filling pattern to be the all-white patternwhen the corrected gradation value is less than the predeterminedthreshold value and to be the black core pattern when the correctedgradation value is greater than or equal to the predetermined thresholdvalue.

The determination of whether or not there is a pixel determined as theblack core pixel in the reference pixels is made, for example, in thefollowing manner.

In one configuration, the pattern determination unit 12 b refers to thepixel value of the pixel of the output image data. When a group ofpixels of the black core pattern is present among the groups of pixelscorresponding to the reference pixels, the pattern determination unit 12b determines that there is a pixel determined as the black core patternin the reference pixels. When, on the other hand, there is no group ofpixels of the black core pattern, the pattern determination unit 12 bdetermines that there is no pixel determined as the black core patternin the reference pixels.

In another configuration, the pattern determination unit 12 b records,in correspondence to each pixel of the input image data, a type of thefilling pattern determined for the pixel as a determination result andrefers to the determination result to determine whether or not there isa pixel determined as the black core pattern in the reference pixels.

In the exemplary embodiment, from the viewpoint of acquiring an imagewith a superior graininess by imparting a periodicity to the arrangementof the dot, the predetermined threshold value is spatially varied in aperiodic manner. In other words, the threshold value which is used fordetermination of whether or not the black core pattern is to begenerated spatially varies in a periodic manner. For example, athreshold value matrix in which multiple threshold values are placed isprepared in advance, and the threshold values of the threshold matrixare sequentially used as the above-described predetermined thresholdvalue. For example, a pattern of the threshold values which spatiallyvaries in a periodic manner (for example, a threshold value matrix) isstored in a threshold value storage 23 in advance, and the conversionunit 12 reads, from the threshold value storage 23, a threshold valuecorresponding to the position of the pixel of interest in the inputimage data and uses the read threshold value.

In a specific configuration of a process for determining the fillingpattern, the filling pattern is determined in the following manner.

(1) When a pixel determined as the black core pattern is present amongthe reference pixels and the corrected gradation value is less than afirst threshold value Th1, the filling pattern is determined to be theblack growth pattern.

(2) When no pixel determined as the black core pattern is present amongthe reference pixels and the corrected gradation value is less than thefirst threshold value Th1, the filling pattern is determined to be theall-white pattern if the corrected gradation value is less than a secondthreshold value Th2 (which is less than Th1) and to be the black corepattern if the corrected gradation value is greater than or equal to thesecond threshold value Th2.

(3) When a pixel determined as a white core pattern is present among thereference pixels and the corrected gradation value is greater than orequal to the first threshold value Th1, the filling pattern isdetermined to be the white growth pattern.

(4) When no pixel determined as the white core pattern is present amongthe reference pixels and the corrected gradation value is greater thanor equal to the first threshold value Th1, the filling pattern isdetermined to be the all-black pattern if the corrected gradation valueis greater than or equal to a third threshold value (which is greaterthan Th1) and to be the white core pattern if the corrected gradationvalue is less than the third threshold value Th3.

In this configuration, the second threshold value Th2 spatially variesin a periodic manner. In one configuration, the third threshold valueTh3 also spatially varies in a periodic manner, but may be a fixedvalue. The first threshold value Th1 is, for example, a fixed value, butmay vary.

For the high-density region (for example, in a case in which thecorrected gradation value is greater than or equal to the firstthreshold value Th1), the binarization method is not limited to thatdescribed above, and another binarization method may be used.

FIG. 3 is a flowchart showing an example conversion process in theexemplary embodiment. An example conversion process will now bedescribed with reference to FIG. 3.

In this example process, the input image data are image data having aresolution of 600×600 dpi and a number of gradations per pixel of 256(with gradation values of 0-255). The output image data are image datahaving a resolution of 2400×2400 dpi and a number of gradations perpixel of 2 (with gradation values of 0-1). The group of pixels of theoutput image data corresponding to a pixel of the input image data is agroup of pixels of 4×4 matrix, and the output image data includes600×600 groups of pixels.

As shown in FIG. 3, the conversion unit 12 acquires the gradation valueCin of the pixel of interest among the input image data (S1).

Then, the conversion unit 12 calculates a sum A of the error valuesdiffused from the peripheral pixels to the pixel of interest (S2). Forexample, the error values of the multiple pixels in the periphery of thepixel of interest P are those shown in FIG. 4 and the error diffusioncoefficients for the multiple pixels in the periphery of the pixel ofinterest P are those shown in FIG. 5. The sum A is calculated in thefollowing manner.

A=10×2/64+2×3/64−30×6/64+2×3/64−20×2/64+20×3/64+30×6/64+5×12/64+10×6/64+10×3/64+10×6/64−40×12/64

Next, the conversion unit 12 adds the sum A to the gradation value Cinof the pixel of interest to calculate the corrected gradation value Ca(=Cin+A) (S3).

Then, the conversion unit 12 determines the filling pattern of the groupof pixels corresponding to the pixel of interest based on the correctedgradation value Ca and the patterns of the reference pixels (S4).

In the present example process, the filling pattern is determined to beone of the all-white pattern, the black core pattern, the black growthpattern, the all-black pattern, the white core pattern, and the whitegrowth pattern. As shown in FIG. 6, the black core pattern is a patternin which 8 pixels at the bottom right corner among the group of pixelsare filled. As shown in FIG. 7, the white core pattern is a pattern inwhich 8 pixels at the bottom right among the group of pixels are notfilled.

In addition, in the present example process, the filling pattern isdetermined by, reference to a first determination map shown in FIG. 8and a second determination map shown in FIG. 9.

Moreover, in the present example process, the reference pixels areprocessed pixels adjacent to the pixel of interest to the left, above,and to the upper left.

FIG. 10 is a flowchart showing an example of the process for determiningthe filling pattern; that is, an example of the process of step S4 ofFIG. 3.

In FIG. 10, the conversion unit 12 determines whether or not thecorrected gradation value Ca is less than a center threshold valueTh_Center (S40).

When it is determined that the corrected gradation value Ca is less thanthe center threshold value Th_Center (S40: YES), the conversion unit 12determines whether or not there is a group of pixels of the black corepattern in the groups of pixels of the output image data correspondingto the three reference pixels adjacent to the pixel of interest (S41).

When it is determined that there is a group of pixels of the black corepattern (S41: YES), the conversion unit 12 determines the fillingpattern of the pixel of interest to be the black growth pattern (S42).Here, the number of black pixels to be filled in the black growthpattern is determined according to the second determination map of FIG.9 and based on the corrected gradation value Ca, and is increased for alarger corrected gradation value Ca. FIG. 11 shows an example in whichthe pixel of interest P is converted to the black growth pattern whenthe group of pixels corresponding to the upper left reference pixel ofthe pixel of interest P is the group of pixels of the black corepattern. In FIG. 11, the black dot is formed by a black pixel of theblack core pattern and the black pixel of the black growth patternadjacent to the black core pattern.

When, on the other hand, it is determined that there is no group ofpixels of the black core pattern (S41: NO), for example, when there isno group of pixels of the black core pattern in the groups of pixelscorresponding to the three reference pixels adjacent to the pixel ofinterest P as shown in FIG. 12, the conversion unit 12 acquires a lowerthreshold value Th1_Low corresponding to the position of the pixel ofinterest in the input image data (S43). More specifically, a thresholdvalue matrix for the lower threshold values as shown in FIG. 13 isstored in the threshold value storage 23 in advance, and the conversionunit 12 reads, from the threshold value storage 23 and as the lowerthreshold value Th1_Low, a threshold value corresponding to the positionof the pixel of interest from among the threshold values in thethreshold value matrix for the lower threshold value. FIG. 14 shows acorrespondence relationship between the pixel of the input image dataand the threshold value. In FIG. 14, each cell indicates a pixel and thevalue in the cell shows a threshold value corresponding to the pixelrepresented by the cell. As shown in FIG. 14, the threshold value matrixis repeatedly used on the input image data.

The conversion unit 12 then determines whether or not the correctedgradation value Ca is greater than or equal to the lower threshold valueTh1_Low (S44).

When it is determined that the corrected gradation value Ca is greaterthan or equal to the lower threshold value Th1_Low (S44: YES), theconversion unit 12 determines the filling pattern of the pixel ofinterest to be the black core pattern (S45).

When, on the other hand, it is determined that the corrected gradationvalue Ca is less than the lower threshold value Th1_Low (S44: NO), theconversion unit 12 determines the filling pattern of the pixel ofinterest to be the all-white pattern (S46).

When it is determined in step S40 that the corrected gradation value Cais not less than the center threshold value Th_Center (S40: NO), theconversion unit 12 determines whether or not there is a group of pixelsof the white core pattern in the groups of pixels of the output imagedata corresponding to the three reference pixels adjacent to the pixelof interest (S51).

When it is determined that there is a group of pixels of the white corepattern (S51: YES), the conversion unit 12 determines the fillingpattern of the pixel of interest to be the white growth pattern (S52).Here, the number of white pixels which are not filled in the whitegrowth pattern is determined according to the second determination mapof FIG. 10 and based on the corrected gradation value Ca, and isincreased for a smaller corrected gradation value Ca. FIG. 15 shows anexample in which the pixel of interest P is converted to the whitegrowth pattern when the group of pixels corresponding to the referencepixel at the upper left of the pixel of interest P is a group of pixelsof the white core pattern. In FIG. 15, the white dot is formed by awhite pixel of the white core pattern and a white pixel of the whitegrowth pattern adjacent to the white core pattern.

When, on the other hand, it is determined that there is no group ofpixels of the white core pattern (S51: NO); for example, when there isno group of pixels of the white core pattern in the groups of pixelscorresponding to the three reference pixels adjacent to the pixel ofinterest P as shown in FIG. 16, the conversion unit 12 acquires an upperthreshold value Th1_High corresponding to the position of the pixel ofinterest in the input image data (S53). More specifically, a thresholdmatrix for the upper threshold value is stored in the threshold valuestorage 23 in advance, and the conversion unit 12 reads, from thethreshold value storage 23 and as the upper threshold value Th1_High, athreshold value corresponding to the position of the pixel of interestfrom among the threshold values in the threshold value matrix for theupper threshold value.

The conversion unit 12 then determines whether or not the correctedgradation value Ca is less than the upper threshold value Th1_High(S54).

When it is determined that the corrected gradation value Ca is less thanthe upper threshold value Th1_High (S54: YES), the conversion unit 12determines the filling pattern of the pixel of interest to be the whitecore pattern (S55).

When, on the other hand, it is determined that the corrected gradationvalue Ca is not less than the upper threshold value Th1_High (S54: NO),the conversion unit 12 determines the filling pattern of the pixel ofinterest to be the all-black pattern (S56).

Referring again to FIG. 3, after the filling pattern is determined instep S4, the conversion unit 12 calculates, as the error value of thepixel of interest, a value in which the gradation value indicated in thefilling pattern of the pixel of interest is subtracted from thecorrected gradation value Ca of the pixel of interest (S5). Morespecifically, the gradation value indicated in the filling pattern isthe gradation value based on an area ratio of the black pixel in theoverall group of pixels. For example, when the number of filling in thefilling pattern of the pixel of interest is k (0≦k≦16), the error valueE of the pixel of interest is calculated by E=Ca−16×k. The conversionunit 12 stores the calculated error value in the error value storage 21.

The conversion unit 12 then determines whether or not the process iscompleted for all pixels of the input image data (S6).

When it is determined that the process is not completed (S6: NO), theconversion unit 12 moves the pixel of interest (S7) and returns theprocess to step S1.

When, on the other hand, it is determined that the process is completedfor all pixels (S6: YES), the conversion process is completed.

In this manner, the filling pattern of the group of pixels of the outputimage data corresponding to each pixel of the input image data isdetermined and the output image data including the collection of thegroups of pixels having the gradation value patterns defined by thefilling patterns are acquired.

Second Exemplary Embodiment

An image processor according to a second exemplary embodiment of thepresent invention will now be described. The image processor of thesecond exemplary embodiment is very similar to the image processor ofthe first exemplary embodiment, and, thus, the portions of the imageprocessor that are identical to those in the first exemplary embodimentare assigned the same reference numerals and their repeated descriptionsare omitted.

In the second exemplary embodiment, from the viewpoint of acquiring adot image having a superior periodicity, at least one of the number ofpredetermined multiple pixels in the black core pattern (that is, thenumber of pixels to be filled) and the number corresponding to thecorrected gradation value in the black growth pattern (that is, thenumber of pixels to be filled) varies according to the gradation valueof the pixel of interest so that the number becomes smaller as thedensity becomes smaller.

More specifically, when the conversion unit 12 determines the fillingpattern of the pixel of interest to be the black core pattern, theconversion unit 12 determines the number of pixels to be filledaccording to the gradation value of the pixel of interest. For example,a table showing a correspondence relationship between the gradationvalue and the number of pixels to be filled is prepared in advance andthe conversion unit 12 reads from the table a number corresponding tothe gradation value of the pixel of interest.

In addition to or in place of the above-described process, theconversion unit 12 may determine, when the conversion unit 12 determinesthe filling pattern of the pixel of interest to be the black growthpattern, the number of the pixels to be filled according to thegradation value of the pixel of interest. For example, in oneconfiguration, a table showing a correspondence relationship between thegradation value and a correction number is prepared in advance, and theconversion unit 12 reads, from the table, a correction numbercorresponding to the gradation value of the pixel of interest, adds thecorrection number to the number determined by the second determinationmap, and acquires the number of pixels to be filled. In anotherconfiguration, multiple types of second determination maps are preparedin advance, and the conversion unit 12 selects a second determinationmap corresponding to the gradation value of the pixel of interest, anddetermines the number of pixels to be filled based on the selectedsecond determination map.

From the viewpoint of imparting superior periodicity to the black dot inthe low-density region (for example, a region in which the density valueis greater than or equal to 0% and less than 50%), an ideal size SB ofthe black dot is determined by a relationship between the resolution D(dpi) of the output image data, a number of lines L of the dot (lpi)determined by the pattern of the threshold value (for example, thethreshold value matrix), and the density value C (%) of the input imagedata, and is represented by the following equation. The number of linesL determined by the threshold value matrix of FIG. 13 is 268 lpi.

$\begin{matrix}{{SB} = {\left( \frac{D}{L} \right)^{2} \times \frac{C}{100}}} & \left\lbrack {{Equation}\mspace{20mu} 2} \right\rbrack\end{matrix}$

If a significant difference exists between the size of the black dotacquired by the conversion process based on the input image data and theideal size of the black dot as described above, the periodicity of thedot may be destroyed.

In consideration of this, in one specific configuration, at least one ofthe number of pixels to be filled in the black core pattern and thenumber of pixels to be filled in the black growth pattern is set so thatthe size of the black dot acquired by the conversion process based onthe input image data is close to, the same as, or approximately the sameas the above-described ideal size of the black dot.

In addition, in one configuration in the exemplary embodiment, from theviewpoint of acquiring a dot image having a superior periodicity in thehigh-density region, at least one of the number of the predeterminedmultiple pixels in the white core pattern (that is, the number of pixelsto not be filled) and the number according to the corrected gradationvalue in the white growth pattern (that is, the number of pixels to notbe filled) varies according to the gradation value of the pixel ofinterest so that the number is decreased as the density is increased.

More specifically, when the conversion unit 12 determines the fillingpattern of the pixel of interest to be the white core pattern, theconversion unit 12 determines the number of pixels to not be filledbased on the gradation value of the pixel of interest. For example, theconversion unit 12 reads, from a table which is prepared in advance, thenumber of pixels to not be filled corresponding to the gradation valueof the pixel of interest.

In addition to or in place of the above-described process, theconversion unit 12 may determine, when the conversion unit 12 determinesthe filling pattern of the pixel of interest to be the white growthpattern, the number of pixels to not be filled according to thegradation value of the pixel of interest. For example, in oneconfiguration, the conversion unit 12 reads a correction numbercorresponding to the gradation value of the pixel of interest from atable which is prepared in advance, adds the correction number to thenumber determined by the second determination map, and acquires thenumber of pixels to not be filled. In another configuration, theconversion unit 12 selects a second determination map corresponding tothe gradation value of the pixel of interest from among multiple typesof second determination maps, and determines the number of pixels to notbe filled based on the selected second determination map.

From the viewpoint of imparting superior periodicity to the white dot inthe high-density region (for example, a region in which the densityvalue is greater than or equal to 50% and less than or equal to 100%),an ideal size SW of the white dot is determined by a relationship of theresolution D (dpi) of the output image data, a number of lines L (lpi)of the dot determined by the pattern of the threshold value (forexample, the threshold value matrix), and the density value C (%) of theinput image data, and is represented by the following equation.

$\begin{matrix}{{SW} = {\left( \frac{D}{L} \right)^{2} \times \frac{\left( {100 - C} \right)}{100}}} & \left\lbrack {{Equation}\mspace{14mu} 3} \right\rbrack\end{matrix}$

If a significant difference exists between the size of the white dotacquired by the conversion process based on the input image data and theabove-described ideal size of the white dot, the periodicity of the dotmay be destroyed.

In consideration of this, in a specific configuration, at least one ofthe number of pixels to not be filled in the white core pattern and thenumber of pixels to not be filled in the white growth pattern is set sothat the size of the white dot acquired by the conversion process basedon the input image data is close to, the same as, or approximately thesame as the ideal size of the white dot.

Third Exemplary Embodiment

An image processor according to a third exemplary embodiment of thepresent invention will now be described. The image processor of thethird exemplary embodiment is similar to the image processor of thesecond exemplary embodiment, and, thus, the portions that are identicalto those in the second exemplary embodiment are assigned the samereference numerals and their repeated descriptions are omitted.

In the third exemplary embodiment, from the viewpoint of acquiring asuperior gradation reproducibility, when the predetermined multiple atleast in the black core pattern varies according to the gradation valueof the pixel of interest, the predetermined multiple is a fixed value inthe low-density region in which the gradation value of the pixel ofinterest is less than a predetermined value.

The fixed value is a value which defines a minimum size of the blackdot, and may be set from the viewpoint of acquiring superior gradationreproducibility.

More specifically, in the present exemplary embodiment, thepredetermined multiple in the black core pattern (number of pixels to befilled) is set to a fixed value in the low-density region in which thegradation value of the pixel of interest is less than the predeterminedvalue so that superior gradation reproducibility can be acquired and isvaried according to the gradation value of the pixel of interest in thedensity region in which the gradation value of the pixel of interest isgreater than or equal to the predetermined value so that a superiorperiodicity of the dot can be acquired.

FIG. 17 is a diagram showing an example setting of a correspondencerelationship between the density value of the pixel of interest and thenumber of black pixels in the black core pattern or the number of whitepixels in the white core pattern. In FIG. 17, in the density region witha density value of greater than or equal to 0% and less than 50%, thenumber of black pixels in the black core pattern is defined, and, in thedensity region with a density value of greater than or equal to 50% andless than or equal to 100%, the number of white pixels in the white corepattern is defined. This example setting configuration is an example inwhich the size of the dot is adjusted by varying the number of the blackpixels in the black core pattern and the number of white pixels in thewhite core pattern in the case in which the output resolution D is 2400dpi and the number of lines L of the dot determined by the pattern ofthe threshold value is 268 lpi. The relationship between the densityvalue C (%) of the pixel of interest and the gradation value G (0-255)of the pixel of interest is represented, for example, by C=G·(100/255).

When input image data with multiple values representing a gradationimage in which the density value gradually changes from 0% to 50% werebinarized by the image conversion process of the third exemplaryembodiment using the threshold value matrix of FIG. 13 and the settingof FIG. 17, output image data shown in FIG. 18 were acquired.

As a comparative example, when the above-described input image data ofmultiple values representing the gradation image were binarized throughthe image conversion process of the first exemplary embodiment using thethreshold value matrix of FIG. 13 and without varying the number ofblack pixels in the black core pattern, output image data shown in FIG.19 were acquired.

In comparison to the image of the comparative example shown in FIG. 19,in the image produced by the third exemplary embodiment shown in FIG.18, superior periodicity of the dot was acquired.

The image processors according to the first through third exemplaryembodiments of the present invention can be applied to various usages,and are, for example, applied to an image formation device (such as aprinter or a copier).

FIG. 20 is a schematic structural diagram showing a structure of animage formation device 100 including an image processor according to anexemplary embodiment of the present invention. The image formationdevice 100 is a device which forms an image on a recording medium suchas paper through electrophotography. The image formation device 100 isan image formation device with multiple colors in FIG. 20, but mayalternatively be an image formation device of a single color.

In FIG. 20, the image formation device 100 includes an image dataacquisition unit 50, image processors 60Y, 60M, 60C, and 60K, and animage formation unit 70.

The image data acquisition unit 50 acquires input image data representedby pixels of M gradations (M≧3). More specifically, the image dataacquisition unit 50 receives an input of PDL (Page Description Language)data from an external information processor (for example, a clientdevice such as a personal computer) or of scan data which are read froma document by a scanner, and converts the input data into bitmap imagedata of 256 gradations of 4 colors (Y, M, C, and K). The image dataacquisition unit 50 outputs the acquired image data of Y, M, C, and Kcolors to the image processors 60Y, 60M, 60C, and 60K, respectively.

Each of the image processors 60Y, 60M, 60C, and 60K has a structuresimilar to that of the image processor of the above-described exemplaryembodiments, and binarizes input image data of 256 gradations which areinput from the image data acquisition unit 50 in a manner similar to theimage processor of the exemplary embodiment, and generates output imagedata of two gradations.

The image formation unit 70 forms an image on a recording medium basedon the output image data acquired by the image processors 60Y, 60M, 60C,and 60K.

More specifically, the image formation unit 70 has photosensitivestructures 71Y, 71M, 71C, and 71K for yellow (Y), magenta (M), cyan (C),and black (K). In the periphery of the photosensitive structures 71Y,71M, 71C, and 71K, charging units 72Y, 72M, 72C, and 72K, exposure units73Y, 73M, 73C, and 73K, and developer units 74Y, 74M, 74C, and 74K areprovided. The four photosensitive structures 71Y, 71M, 71C, and 71K areplaced in parallel to each other along a paper transport direction(direction of an arrow X in FIG. 20), and a transfer belt 75 is providedto contact the photosensitive structures. In addition, downstream alongthe paper transport direction of the four photosensitive structures, afixation unit 76 is placed.

The charging units 72Y, 72M, 72C, and 72K uniformly charge the surfacesof the photosensitive structures 71Y, 71M, 71C, and 71K, respectively.

The exposure units 73Y, 73M, 73C, and 73K irradiate the surfaces of theuniformly charged photosensitive structures 71Y, 71M, 71C, and 71K witha laser beam to form an electrostatic latent image. More specifically,the exposure units 73Y, 73M, 73C, and 73K control ON/OFF of theirradiation of the laser beam, respectively, based on the output imagedata of the two gradations which are input from the image processors60Y, 60M, 60C, and 60K, respectively, so that electrostatic latentimages corresponding to the output image data are formed on thephotosensitive structures.

The developer units 74Y, 74M, 74C, and 74K develop the electrostaticlatent images formed on the photosensitive structures 71Y, 71M, 71C, and71K with toners of Y, M, C, and K colors, respectively.

The toner images of Y, M, C, and K colors formed on the photosensitivestructures 71Y, 71M, 71C, and 71K are sequentially transferred to arecording medium such as paper transported on the transfer belt 75. Therecording medium on which the toner images of the Y, M, C, and K colorsare transferred is transported to the fixation unit 76, and the tonerimage is fixed on the recording medium in the fixation unit 76.

The foregoing description of the exemplary embodiments of the presentinvention has been provided for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit theinvention to the precise forms disclosed. Obviously, many modificationsand variations will be apparent to practitioners skilled in the art. Theexemplary embodiments were chosen and described in order to best explainthe principles of the invention and its practical applications, therebyenabling others skilled in the art to understand the invention forvarious embodiments and with various modifications as are suited to theparticular use contemplated. It is intended that the scope of theinvention be defined by the following claims and their equivalents.

For example, when the input image data includes multiple colorcomponents, the image processor may binarize each color component in amanner described above. In this case, from the viewpoint of reducingcolor unevenness due to interference of screens, the pattern of thethreshold value (for example, the threshold value matrix) may be set sothat the arrangement direction of the dot in the output image datadiffers for each color component. Alternatively, the pattern of thethreshold value (for example, the threshold value matrix) may be set sothat the period of the arrangement of the dot in the output image datadiffers for each color component. In this case, from the viewpoint ofacquiring a superior periodicity, the number of black pixels in theblack core pattern and the black growth pattern may be set, for eachcolor component, according to the period of the dot of the colorcomponent.

In the above-described exemplary embodiments, the filling patternsinclude the first through third patterns, but it is also possible toprovide an image processor in which the second pattern is omitted. Inother words, an image processor having at least the first pattern andthe third pattern as the filling pattern may be provided. In this imageprocessor, the pattern determination unit determines the filling patternto be the first or third pattern according to a size relationship of thecorrected gradation value and the predetermined threshold value whichspatially varies in a periodic manner, for example, regardless ofwhether or not a pixel determined as the black core pattern is presentamong the reference pixels.

1. An image processor comprising: a gradation value acquisition unitthat acquires a gradation value of a pixel of interest which is a pixelsequentially selected as a target of a binarization process from inputimage data represented by pixels of M gradations, wherein M≧3; and apattern determination unit that determines a filling pattern of a groupof pixels of output image data corresponding to the pixel of interestaccording to a corrected gradation value acquired by adding, to thegradation value of the pixel of interest, an error value diffused from apixel at a periphery of the pixel of interest, wherein the fillingpattern includes at least a first pattern in which a predeterminedplurality of pixels are filled and which forms a core of a dot and athird pattern in which substantially no pixel is filled and the patterndetermination unit determines the filling pattern to be one of the firstpattern and the third pattern according to a size relationship betweenthe corrected gradation value and a predetermined threshold value whichspatially varies in a periodic manner.
 2. The image processor accordingto claim 1, wherein the filling pattern includes a second pattern inwhich a number of pixels are filled, the number corresponding to thecorrected gradation value, and which forms a dot with the first pattern,and the pattern determination unit determines the filling pattern to bethe second pattern when a pixel determined to be the first pattern ispresent among predetermined pixels adjacent to the pixel of interest,and determines the filling pattern to be one of the first pattern andthe third pattern according to the size relationship between thecorrected gradation value and the predetermined threshold value when nopixel determined to be the first pattern is present among thepredetermined pixels.
 3. The image processor according to claim 2,wherein at least one of the number of pixels to be filled in the firstpattern and the number of pixels to be filled in the second patternvaries according to the gradation value of the pixel of interest so thatthe number becomes smaller as a density becomes smaller.
 4. The imageprocessor according to claim 3, wherein when at least the number ofpixels to be filled in the first pattern varies according to thegradation value of the pixel of interest, the number of pixels to befilled in the first pattern is a fixed value in a low-density region inwhich the gradation value of the pixel of interest is less than apredetermined value.
 5. An image formation device comprising: an imagedata acquisition unit that acquires input image data represented bypixels of M gradations, wherein M≧3; an image processor that convertsthe input image data into output image data represented by pixels of twogradations; and an image formation unit that forms an image based on theoutput image data on a recording medium, wherein the image processorcomprises: a gradation value acquisition unit that acquires a gradationvalue of a pixel of interest which is a pixel sequentially selected as atarget of a binarization process from the input image data; and apattern determination unit that determines a filling pattern of a groupof pixels of output image data corresponding to the pixel of interestaccording to a corrected gradation value acquired by adding, to thegradation value of the pixel of interest, an error value diffused from apixel at a periphery of the pixel of interest, wherein the fillingpattern includes at least a first pattern in which a predeterminedplurality of pixels are filled and which forms a core of a dot and athird pattern in which substantially no pixel is filled and the patterndetermination unit determines the filling pattern to be one of the firstpattern and the third pattern according to a size relationship betweenthe corrected gradation value and a predetermined threshold value whichspatially varies in a periodic manner.
 6. A method of processing animage, the method comprising: acquiring a gradation value of a pixel ofinterest which is a pixel sequentially selected as a target of abinarization process from input image data represented by pixels of Mgradations, wherein M≧3; and determining a filling pattern of a group ofpixels of output image data corresponding to the pixel of interestaccording to a corrected gradation value acquired by adding, to thegradation value of the pixel of interest, an error value diffused from apixel at a periphery of the pixel of interest, wherein the fillingpattern includes at least a first pattern in which a predeterminedplurality of pixels are filled and which forms a core of a dot and athird pattern in which substantially no pixel is filled, and thedetermining the pattern includes determining the filling pattern to beone of the first pattern and the third pattern according to a sizerelationship between the corrected gradation value and a predeterminedthreshold value which spatially varies in a periodic manner.
 7. Acomputer-readable medium storing a program causing a computer to executea process for processing an image, the process comprising: acquiring agradation value of a pixel of interest which is a pixel sequentiallyselected as a target of a binarization process from input image datarepresented by pixels of M gradations, wherein M≧3; and determining afilling pattern of a group of pixels of output image data correspondingto the pixel of interest according to a corrected gradation valueacquired by adding, to the gradation value of the pixel of interest, anerror value diffused from a pixel at a periphery of the pixel ofinterest, wherein the filling pattern includes at least a first patternin which a predetermined plurality of pixels are filled and which formsa core of a dot and a third pattern in which substantially no pixel isfilled, and the determining the pattern includes determining the fillingpattern to be one of the first pattern and the third pattern accordingto a size relationship between the corrected gradation value and apredetermined threshold value which spatially varies in a periodicmanner.
 8. The computer-readable medium according to claim 7, whereinthe filling pattern includes a second pattern in which a number ofpixels are filled, the number corresponding to the corrected gradationvalue, and which forms the dot with the first pattern, and thedetermining the pattern includes determining the filling pattern to bethe second pattern when a pixel determined to be the first pattern ispresent among predetermined pixels adjacent to the pixel of interest,and determining the filling pattern to be one of the first pattern andthe third pattern according to the size relationship between thecorrected gradation value and the predetermined threshold value when nopixel determined to be the first pattern is present among thepredetermined pixels.
 9. The computer-readable medium according to claim8, wherein at least one of the number of pixels to be filled in thefirst pattern and the number of pixels to be filled in the secondpattern varies according to the gradation value of the pixel of interestso that the number becomes smaller as a density becomes smaller.
 10. Thecomputer-readable medium according to claim 9, wherein when at least thenumber of pixels to be filled in the first pattern varies according tothe gradation value of the pixel of interest, the number of pixels to befilled in the first pattern is a fixed value in a low-density region inwhich the gradation value of the pixel of interest is less than apredetermined value.